High-Throughput Computational Screening of Cubic Perovskites for Solid Oxide Fuel Cell Cathodes

16 March 2021, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


It is a present-day challenge to design and develop oxygen permeable solid oxide fuel cell (SOFC) electrode and electrolyte materials that operate at low temperatures. Herein, by performing high-throughput density functional theory (HT-DFT) calculations, oxygen vacancy formation energy, Evac, data for a pool of all-inorganic ABO3 and AI0.5AII0.5BO3 cubic perovskites is generated. Using Evac data of perovskites, the area-specific resistance (ASR) data, which is related to both oxygen reduction reaction activity and selective oxygen ion conductivity of materials, is calculated. Screening a total of 270 chemical compositions, 31 perovskites are identified as candidates with properties that are in between state-of-the-art SOFC cathode and oxygen permeation components. In addition, an intuitive approach to estimate Evac and ASR data of complex perovskites solely by using the easy-to-access data of simple perovskites is shown, which is expected to boost future explorations on perovskite material search space for genuinely diverse energy applications.


Solid Oxide Fuel Cells
Density Functional Theory

Supplementary materials

2021-03-14 - Tezsevin et.al. - High-throughput computational screening of cubic perovskites for solid oxide fuel cell cathodes - SI


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